Month and Year Data

Column

Month Referrals Bar Graph

Month Referral Table

Total Number of CMT Referrals by Month
Referral Month Sex Total
January Female 7
January Male 6
February Female 4
February Male 3
March Female 2
March Male 1
April Female 5
April Male 3
May Female 3
May Male 1
June Female 3
July Female 5
July Male 1
August Male 1
September Female 8
September Male 1
October Female 5
October Male 3
November Female 4
November Male 3
December Female 9
December Male 5

Month Referrals Line Plot

Column

Year Referrals

Year Referral Table

Total Number of CMT Referrals by Year
Referral Year Sex Total
2018 Female 20
2018 Male 11
2019 Female 28
2019 Male 13
2020 Female 7
2020 Male 4

School Referrals

Column

School Referral Plot

School Referral Table

Total Number of CMT Referrals per School
School Total
Churchill H.S. 5
College Student 9
Cottage Grove H.S. 2
Creswell H.S. 1
Elmira H.S. 2
North Eugene H.S. 4
Other 24
Pleasant Hill H.S. 2
Sheldon H.S. 5
South Eugene H.S. 7
Springfield H.S. 6
Thurston H.S. 7
Willamette H.S. 9

CMT Referral Stats

CMT Referral Status

---
title: "CMT Data"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
    vertical_layout: scroll
    theme: cerulean
---

```{r setup, include=FALSE}
library(flexdashboard)
library(rio)
library(here)
library(tidyverse)
library(knitr)
library(kableExtra)
library(ggrepel)
library(colorblindr)
library(gt)
library(plotly)
library(reactable)

opts_chunk$set(echo = FALSE,
               fig.width = 6.5,
               fig.height = 8)

theme_set(theme_minimal(15))

```

# Month and Year Data 

Description of Data {.sidebar}
--------

This data has been collected from January 2018 to the present through collaboration of the Eugene Youth Concussion Management Team (CMT) 
```{r load-data, fig.width = 10, fig.height = 10, echo = FALSE, include=FALSE}
cmt <- import(here("data", "cmt_data.sav"),
               setclass = "tbl_df") %>% 
  characterize() %>% 
  janitor::clean_names() 

head(cmt)

cmt <- cmt %>% 
  rename(HEDCO = hedco_referral,
         PT = pt_referral,
         STRONG = psych_referral,
         CBIRT = cbirt_referral,
         Neurology = neuro_referral)


cmt$referral_month <- factor(cmt$referral_month, levels = c("January",
                                                            "February",
                                                            "March",
                                                            "April",
                                                            "May",
                                                            "June",
                                                            "July",
                                                            "August",
                                                            "September",
                                                            "October",
                                                            "November",
                                                            "December"))

cmt$referral_year <- factor(cmt$referral_year, levels = c("2018", "2019", "2020"))

```

Column {.tabset data-height=1000}
-----------------------------------------------------------------------

### Month Referrals Bar Graph 

```{r month plot 1}

plot_1 <- ggplot(cmt, aes(referral_month)) +
  geom_bar(aes(fill = referral_year)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_text(aes(label = ..count..), 
            stat = "count", 
            size = 4,
            nudge_y = -0.5,
            color = "white") +
  theme_minimal() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5)) +
  theme(axis.text.x = element_text(angle = 45),
        axis.text = element_text(size = 12),
        axis.title=element_text(size=12),
        legend.text = element_text(size = 12)) +
  labs(x = "Month",
       y = "Total",
       fill = "Referral \nYear",
       title = "Number of CMT Referrals by Month") 

ggplotly(plot_1)

```

### Month Referral Table
```{r month table}
cmt_descriptives_month <- cmt %>% 
  group_by(referral_month, sex) %>% 
  summarize(n=n())

knitr::kable(cmt_descriptives_month,
             caption = "Total Number of CMT Referrals by Month",
             col.names = c("Referral Month",
                           "Sex",
                           "Total")) %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"))

```

### Month Referrals Line Plot
```{r month line plot}
cmt_count <- cmt %>% 
  count(referral_month)

ggplot(cmt_count, aes(referral_month, n, group = 1)) +
  geom_area(fill = "cornflowerblue",
            alpha = 0.3) +
  geom_line(lwd = 1.6, 
            color = "gray40") +
  geom_point(color = "blue",
             size = 3) +
  geom_smooth(color = "magenta",
              lwd = 1.4,
              se = FALSE) +
  geom_text_repel(aes(label = n, group = 1)) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5)) +
   theme(axis.text.x = element_text(angle = 45),
         axis.text = element_text(size = 12),
        axis.title=element_text(size=12)) +
  labs(x = "Referral Month",
       y = "Total",
       title = "CMT Referrals by Month")

```

Column {.tabset data-width=500}
-----------------------------------------------------------------------

### Year Referrals

```{r sex plot}

pd <- position_dodge(width = 1) 


cmt %>% 
 count(sex, referral_year) %>% 
 ggplot(aes(referral_year, n)) +
  geom_col(aes(fill = sex), position = pd) +
  scale_fill_OkabeIto() +
  geom_text(aes(label = n, group = sex), 
            position = pd,
            hjust = 2,
            size = 5,
            color = "white") +
  theme_minimal() +
  coord_flip() +
  scale_x_discrete(limits = rev(levels(cmt$referral_year))) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 12),
        axis.title = element_text(size=12),
        legend.text = element_text(size = 12)) +
  guides(fill = guide_legend(reverse = TRUE)) +
  labs(x = "Referral Year",
       y = "Total",
       fill = "Sex",
       title = "Number of CMT Referrals per Year by Sex")


```

### Year Referral Table
```{r referral year table} 
cmt_descriptives_year <- cmt %>% 
  group_by(referral_year, sex) %>% 
  summarize(n=n())

knitr::kable(cmt_descriptives_year,
             caption = "Total Number of CMT Referrals by Year",
             col.names = c("Referral Year",
                           "Sex",
                           "Total")) %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>% 
  row_spec(1, color = "white", background = "#D7261E") %>% 
  row_spec(3, color = "white", background = "#D7261E") %>% 
  row_spec(5, color = "white", background = "#D7261E")

```


# School Referrals

Column {.tabset data-width=750}
-----------------------------------------------------------------------


### School Referral Plot
```{r school referral plot}
ggplot(cmt, aes(fct_rev(fct_infreq(school)))) +
  geom_bar(fill = "#56B4E9",
           color = "white",
           alpha = 0.9) +
   geom_text(aes(label = ..count..), stat = "count", 
            size = 4,
            nudge_y = -0.7,
            color = "white") +
  facet_wrap(~sex, ncol = 1) +
  coord_flip() + 
   theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
         axis.text = element_text(size = 12),
        axis.title=element_text(size=12)) +
   labs(x = "Referral School",
       y = "Total",
       title = "Number of CMT Referrals per School")

```

### School Referral Table
```{r school referral table}
cmt_descriptives_school <- cmt %>% 
  group_by(school) %>% 
  summarize(n=n())

knitr::kable(cmt_descriptives_school,
             caption = "Total Number of CMT Referrals per School",
             col.names = c("School",
                           "Total")) %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed"))

```


# CMT Referral Stats

### CMT Referral Status

```{r referral status plot}
cmt_discipline_referral <- cmt %>% 
  pivot_longer(cols = c("HEDCO",
                        "PT",
                        "STRONG",
                        "CBIRT",
                        "Neurology"),
               names_to = "referral",
               values_to = "status")

cmt_discipline_referral$status <- factor(cmt_discipline_referral$status, levels = c("Yes",
                                                                                    "No"))

plot_3 <- ggplot(cmt_discipline_referral, aes(x = referral)) +
  geom_bar(aes(fill = status), position = "dodge") +
  scale_fill_brewer(palette = "Set2") +
  theme_minimal() +
  coord_flip() +
  scale_x_discrete(limits = rev(levels(cmt_discipline_referral$referral))) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 12),
        axis.title = element_text(size=12),
        legend.text = element_text(size = 12)) +
  guides(fill = guide_legend(reverse = TRUE)) +
  labs(x = "Referral Discipline", 
       y = "Total",
       title = "Referral Status for Clients Enterting CMT Tracking",
       fill = "Referral \nStatus")

ggplotly(plot_3, tooltip = "all")

```